Optimal intraday power trading for single-price balancing markets: An adaptive risk-averse strategy using mixture models
Robin Bruneel,
Mathijs Schuurmans and
Panagiotis Patrinos
Applied Energy, 2025, vol. 389, issue C, No S0306261925004842
Abstract:
Efficient markets are characterized by profit-driven participants continuously refining their positions towards the latest insights. Margins for profit generation are generally small, shaping a difficult landscape for automated trading strategies. This paper introduces a novel intraday power trading strategy tailored for single-price balancing markets. The strategy relies on a strategically devised mixture model to forecast future system imbalance prices and is formulated as a stochastic optimization problem with decision-dependent distributions to address two primary challenges: (i) the impact of trading positions on the system imbalance price and (ii) the uncertainty inherent in the model. The first challenge is tackled by adjusting the model to account for price changes after taking a position. For the second challenge, a coherent risk measure is added to the cost function to take additional uncertainties into account. This paper introduces a methodology to select the tuning parameter of this risk measure adaptively by continuously quantifying the performance of the strategy on a window of recently observed data. The strategy is validated with a simulation on the Belgian electricity market using real-time market data. The adaptive tuning approach leads to higher absolute profits, while also reducing the number of trades.
Keywords: Balancing markets; Electricity trading; Mixture models; Risk management; Stochastic optimization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261925004842
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:389:y:2025:i:c:s0306261925004842
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2025.125754
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().